Classification of Data Mining with Adaboost Method in Determining Credit Providing for Customers

I Gusti Ngurah Agung Surya Mahendra (Department of Electrical and Computer Engineering, Post Graduate Program, Udayana University)
Ida Bagus Leo Mahadya Suta (Department of Electrical and Computer Engineering, Post Graduate Program, Udayana University)
Made Sudarma (Department of Electrical and Computer Engineering, Udayana University)

International Journal of Engineering and Emerging Technology
Vol 4 No 1 (2019): January - June

Credit is the provision of funds for lending and borrowing transactions with the agreement and agreement between the bank or financial institution and its customers, and requires the borrower to pay the debt within a certain period of time and provide services. Crediting is done by identifying and assessing factors that influence credit risk. The loss of income and the threat of profitability are things that need to be wary of lending. Data mining classification can be used to help credit analysts in determining lending to customers. The classification process is carried out to obtain determinant attributes. The results of the classification process are evaluated using the adaboost method and testing using weka to obtain cross validation, confusion matrix to determine the most accurate classification in determining credit for cooperative customers